Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain.

A, Rodríguez; M, Ruiz-Botella; I, Martín-Loeches; Herrera M, Jimenez; J, Solé-Violan; J, Gómez; M, Bodí; S, Trefler; E, Papiol; E, Díaz; B, Suberviola; M, Vallverdu; E, Mayor-Vázquez; Moreno A, Albaya; Berlanga A, Canabal; M, Sánchez; Valle Ortíz M, Del; JC, Ballesteros; Iglesias L, Martín; J, Marín-Corral; Ramos E, López; Valverde V, Hidalgo; Tello LV, Vidaur; Chinesta S, Sancho; de Molina FJ, Gonzáles; García S, Herrero; Pérez CC, Sena; Laderas JC, Pozo; García R, Rodríguez; A, Estella; R, Ferrer

doi:10.1186/s13054-021-03487-8

Public

Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain.

Shared by NobleBlocks on Feb 15, 2021 • 12:00 AM UTC

Authors:

Rodríguez A

Ruiz-Botella M

Martín-Loeches I

Abstract

Background The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes.Methods Prospective, multicenter, observational stud...

Subject

Prognosis

Phenotypes

risk factors

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